Consider the following regression model: t = - 49.4664 + 0.88544X2t + 0.09253X3t; R2 = 0.9979; d

Question:

Consider the following regression model:
Ŷt = - 49.4664 + 0.88544X2t + 0.09253X3t; R2 = 0.9979; d = 0.8755
t = (- 2.2392) (70.2936) (2.6933)
where
Y = the personal consumption expenditure (1982 billions of dollars)
X2 = the personal disposable income (1982 billions of dollars) (PDI)
X3 = the Dow Jones Industrial Average Stock Index
The regression is based on U.S. data from 1961 to 1985.
a. Is there first-order autocorrelation in the residuals of this regression? How do you know?
b. Using the Durbin two-step procedure, the preceding regression was trans-formed per Eq. (10.15), yielding the following results:
Yt* = - 17.97 + 0.89X*2t + 0.09X*3t; R2 = 0.9816; d = 2.28
t = (30.72) (2.66)
Has the problem of autocorrelation been resolved? How do you know?
c. Comparing the original and transformed regressions, the t value of the PDI has dropped dramatically. What does this suggest?
d. Is the d value from the transformed regression of any value in determining the presence, or lack thereof, of autocorrelation in the transformed data?